Recognizing 3-D Objects Using 2-D Images

We discuss a strategy for visual recognition by forming groups of salient image features, and then using these groups to index into a data base to find all of the matching groups of model features. We discuss the most space efficient possible method of representing 3-D models for indexing from 2-D data, and show how to account for sensing error when indexing. We also present a convex grouping method that is robust and efficient, both theoretically and in practice. Finally, we combine these modules into a complete recognition system, and test its performance on many real images.

Finding Edges and Lines in Images

The problem of detecting intensity changes in images is canonical in vision. Edge detection operators are typically designed to optimally estimate first or second derivative over some (usually small) support. Other criteria such as output signal to noise ratio or bandwidth have also been argued for. This thesis is an attempt to formulate a set of edge detection criteria that capture as directly as possible the desirable properties of an edge operator. Variational techniques are used to find a solution over the space of all linear shift invariant operators. The first criterion is that the detector have low probability of error i.e. failing to mark edges or falsely marking non-edges. The second is that the marked points should be as close as possible to the centre of the true edge. The third criterion is that there should be low probability of more than one response to a single edge. The technique is used to find optimal operators for step edges and for extended impulse profiles (ridges or valleys in two dimensions). The extension of the one dimensional operators to two dimentions is then discussed. The result is a set of operators of varying width, length and orientation. The problem of combining these outputs into a single description is discussed, and a set of heuristics for the integration are given.

Fragments of place : revealing sense of place through shared phone images.

Is an interactive new media art installation that explores how the sharing of images, normally hidden on mobile phones, can reveal more about people's sense of place and this ultimately shared experience. Traditional views on sense of place, as exemplified by Wagner (1972) and Relph (1976), characterise the experience as a fusion of meaning, act and context. Indeed, Relph suggests that it is not just the identity of a place that is important, but also the identity that a person or group has with that place, in particular whether they are experiencing it as an ‘insider’ or ‘outsider’. This work stimulates debate concerning the impact of technology on sense of place. Technology offers a number of bridges between the real and virtual worlds, but in so doing places an increased tension on the sense of place and subsequently the identity of the individual. This, coupled with the increased use of camera phones, has enabled the documentation of all aspects of our lives, the things we do, the objects we encounter and the places we inhabit. The installation taps into these hidden electronic resources by letting people share their sense of place associated with a large scale event. The work explores the changing nature of the sense of place of performers, visitors and residents over the duration of the event. Interaction with the installation will transform the viewer into performer, echoing Relph’s insider-outsider dichotomy

Festival Images: brand image and stakeholders' brand relationship types at the Edinburgh Festival Fringe.

The Edinburgh Festival Fringe (The Fringe) is the largest arts festival in the world and it has inspired the creation of similar festivals world-wide. Since its conception in 1947, the Fringe has demonstrated significant growth in visitor numbers; ticket sales; and its economic contribution. Despite this, the sustainable future of Edinburgh’s festivals is debated as Edinburgh, ‘the Festival City’, faces threats from other festival destinations. Festivals position Edinburgh creatively in contrast to the city’s traditionally perceived image as a cultural-historic centre. Despite this, little research has been undertaken into the creative and cultural significance of Edinburgh’s festivals, including the Fringe. This interdisciplinary research grounded in marketing, tourism, and festival and event management; and underpinned by constructivism, presents an understanding of types of brand relationships that exist between the Fringe and its primary stakeholders. This is achieved through defining both the Fringe brand image and its primary stakeholders; and applying these definitions to the development of a typology of Fringe-stakeholders’ brand relationships. The significance of this study is evident within its topic of inquiry and the research methods applied. In the little-considered arena of arts festivals and their stakeholders, this is the first in-depth study into the Fringe as a festival and festival brand. Within this, the definition of a Fringe brand image contributes to understanding the cultural and creative significance of the Fringe. Furthermore, this research contributes a unique understanding of the types of stakeholders that are engaged with the Fringe. The types of brand relationships that exist between these stakeholders and the Fringe are another significant contribution to knowledge and understanding. While specific to the present context, these findings may prove transferable to further festivals or events, and related areas and industries. The contribution made by this research to the methodological developments in festival and event studies is of additional significance. The application of visual research methods, including semiotic analysis and photo-elicitation within phenomenological interviews, has previously been applied in marketing, consumer, and tourism research, but not to the understanding of festival brands and stakeholders’ brand relationship types. Findings of this research illustrate that existing marketing and consumer brand frameworks and stakeholder theories are applicable to festivals. Further, it is possible to define ‘a’ Fringe brand image which is subjective and contradictory. The unique open-access and organic, operational model of the Fringe facilitates its many contributors, and consumers. Fringe stakeholders may be categorised according to their level of engagement with the Fringe (as primary or secondary) and their particular stakeholder role(s), which are varied and multiple. Fringe-stakeholder brand relationship types are overwhelmingly positive; and are based upon interpersonal relationship dimensions (including friendships, marriages, kinships and partnerships). Fringe-stakeholder brand relationship types can be classified therefore as having similar dimensions to those brand relationship types previously described for consumer products and brands.

The Depiction of Coronal Structure in White-Light Images

Morgan, Huw, Habbal, S.R., Woo, R., (2006) 'The Depiction of Coronal Structure in White-Light Images', Solar Physics 236(2) pp.263-272 RAE2008

Linear structures in mammographic images: detection and classification

R. Zwiggelaar, S.M. Astley, C.J. Taylor and C.R.M. Boggis, 'Linear structures in mammographic images: detection and classification', IEEE Transaction on Medical Imaging 23 (9), 1077-1086 (2004)

Words, Images, Enemies : Securitization and International Politics

Williams, Mike, 'Words, Images, Enemies: Securitization and International Politics', International Studies Quarterly (2003) 47(4) pp.511-531 RAE2008

Religion and the life attitudes and self-images of American adolescents

The purpose of the project is to research the shape and influence of religion and spirituality in the lives of U.S. adolescents; to identify effective practices in the religious, moral, and social formation of the lives of youth; to describe the extent to which youth participate in and benefit from the programs and opportunities that religious communities are offering to their youth; and to foster an informed national discussion about the influence of religion in youth's lives, in order to encourage sustained reflection about and rethinking of our cultural and institutional practices with regard to youth and religion.

Head Tracking via Robust Registration in Texture Map Images

A novel method for 3D head tracking in the presence of large head rotations and facial expression changes is described. Tracking is formulated in terms of color image registration in the texture map of a 3D surface model. Model appearance is recursively updated via image mosaicking in the texture map as the head orientation varies. The resulting dynamic texture map provides a stabilized view of the face that can be used as input to many existing 2D techniques for face recognition, facial expressions analysis, lip reading, and eye tracking. Parameters are estimated via a robust minimization procedure; this provides robustness to occlusions, wrinkles, shadows, and specular highlights. The system was tested on a variety of sequences taken with low quality, uncalibrated video cameras. Experimental results are reported.

On Clustering Images Using Compression

The need for the ability to cluster unknown data to better understand its relationship to know data is prevalent throughout science. Besides a better understanding of the data itself or learning about a new unknown object, cluster analysis can help with processing data, data standardization, and outlier detection. Most clustering algorithms are based on known features or expectations, such as the popular partition based, hierarchical, density-based, grid based, and model based algorithms. The choice of algorithm depends on many factors, including the type of data and the reason for clustering, nearly all rely on some known properties of the data being analyzed. Recently, Li et al. proposed a new universal similarity metric, this metric needs no prior knowledge about the object. Their similarity metric is based on the Kolmogorov Complexity of objects, the objects minimal description. While the Kolmogorov Complexity of an object is not computable, in "Clustering by Compression," Cilibrasi and Vitanyi use common compression algorithms to approximate the universal similarity metric and cluster objects with high success. Unfortunately, clustering using compression does not trivially extend to higher dimensions. Here we outline a method to adapt their procedure to images. We test these techniques on images of letters of the alphabet.

A Laminar Cortical Model for 3D Perception of Slanted and Curved Surfaces and of 2D Images: Developement, attention, and Bistability

A model of laminar visual cortical dynamics proposes how 3D boundary and surface representations of slated and curved 3D objects and 2D images arise. The 3D boundary representations emerge from interactions between non-classical horizontal receptive field interactions with intracorticcal and intercortical feedback circuits. Such non-classical interactions contextually disambiguate classical receptive field responses to ambiguous visual cues using cells that are sensitive to angles and disparity gradients with cortical areas V1 and V2. These cells are all variants of bipole grouping cells. Model simulations show how horizontal connections can develop selectively to angles, how slanted surfaces can activate 3D boundary representations that are sensitive to angles and disparity gradients, how 3D filling-in occurs across slanted surfaces, how a 2D Necker cube image can be represented in 3D, and how bistable Necker cuber percepts occur. The model also explains data about slant aftereffects and 3D neon color spreading. It shows how habituative transmitters that help to control developement also help to trigger bistable 3D percepts and slant aftereffects, and how attention can influence which of these percepts is perceived by propogating along some object boundaries.

A Neuromorphic Model for Achromatic and Chromatic Surface Representation of Natural Images

This study develops a neuromorphic model of human lightness perception that is inspired by how the mammalian visual system is designed for this function. It is known that biological visual representations can adapt to a billion-fold change in luminance. How such a system determines absolute lightness under varying illumination conditions to generate a consistent interpretation of surface lightness remains an unsolved problem. Such a process, called "anchoring" of lightness, has properties including articulation, insulation, configuration, and area effects. The model quantitatively simulates such psychophysical lightness data, as well as other data such as discounting the illuminant, the double brilliant illusion, and lightness constancy and contrast effects. The model retina embodies gain control at retinal photoreceptors, and spatial contrast adaptation at the negative feedback circuit between mechanisms that model the inner segment of photoreceptors and interacting horizontal cells. The model can thereby adjust its sensitivity to input intensities ranging from dim moonlight to dazzling sunlight. A new anchoring mechanism, called the Blurred-Highest-Luminance-As-White (BHLAW) rule, helps simulate how surface lightness becomes sensitive to the spatial scale of objects in a scene. The model is also able to process natural color images under variable lighting conditions, and is compared with the popular RETINEX model.

Processing of Synthetic Aperture Radar Images by a Multiscale Boundary Contour System and Feature Contour System

An improved Boundary Contour System (BCS) and Feature Contour System (FCS) neural network model of preattentive vision is applied to large images containing range data gathered by a synthetic aperture radar (SAR) sensor. The goal of processing is to make structures such as motor vehicles, roads, or buildings more salient and more interpretable to human observers than they are in the original imagery. Early processing by shunting center-surround networks compresses signal dynamic range and performs local contrast enhancement. Subsequent processing by filters sensitive to oriented contrast, including short-range competition and long-range cooperation, segments the image into regions. The segmentation is performed by three "copies" of the BCS and FCS, of small, medium, and large scales, wherein the "short-range" and "long-range" interactions within each scale occur over smaller or larger distances, corresponding to the size of the early filters of each scale. A diffusive filling-in operation within the segmented regions at each scale produces coherent surface representations. The combination of BCS and FCS helps to locate and enhance structure over regions of many pixels, without the resulting blur characteristic of approaches based on low spatial frequency filtering alone.

Processing of Synthetic Aperture Radar Images by the Boundary Contour System and Feature Contour System

An improved Boundary Contour System (BCS) and Feature Contour System (FCS) neural network model of preattentive vision is applied to two large images containing range data gathered by a synthetic aperture radar (SAR) sensor. The goal of processing is to make structures such as motor vehicles, roads, or buildings more salient and more interpretable to human observers than they are in the original imagery. Early processing by shunting center-surround networks compresses signal dynamic range and performs local contrast enhancement. Subsequent processing by filters sensitive to oriented contrast, including short-range competition and long-range cooperation, segments the image into regions. Finally, a diffusive filling-in operation within the segmented regions produces coherent visible structures. The combination of BCS and FCS helps to locate and enhance structure over regions of many pixels, without the resulting blur characteristic of approaches based on low spatial frequency filtering alone.

An investigation of post-primary students' images of mathematics

This research study investigates the image of mathematics held by 5th-year post-primary students in Ireland. For this study, “image of mathematics” is conceptualized as a mental representation or view of mathematics, presumably constructed as a result of past experiences, mediated through school, parents, peers or society. It is also understood to include attitudes, beliefs, emotions, self-concept and motivation in relation to mathematics. This study explores the image of mathematics held by a sample of 356 5th-year students studying ordinary level mathematics. Students were aged between 15 and 18 years. In addition, this study examines the factors influencing students‟ images of mathematics and the possible reasons for students choosing not to study higher level mathematics for the Leaving Certificate. The design for this study is chiefly explorative. A questionnaire survey was created containing both quantitative and qualitative methods to investigate the research interest. The quantitative aspect incorporated eight pre-established scales to examine students‟ attitudes, beliefs, emotions, self-concept and motivation regarding mathematics. The qualitative element explored students‟ past experiences of mathematics, their causal attributions for success or failure in mathematics and their influences in mathematics. The quantitative and qualitative data was analysed for all students and also for students grouped by gender, prior achievement, type of post-primary school attending, co-educational status of the post-primary school and the attendance of a Project Maths pilot school. Students‟ images of mathematics were seen to be strongly indicated by their attitudes (enjoyment and value), beliefs, motivation, self-concept and anxiety, with each of these elements strongly correlated with each other, particularly self-concept and anxiety. Students‟ current images of mathematics were found to be influenced by their past experiences of mathematics, by their mathematics teachers, parents and peers, and by their prior mathematical achievement. Gender differences occur for students in their images of mathematics, with males having more positive images of mathematics than females and this is most noticeable with regards to anxiety about mathematics. Mathematics anxiety was identified as a possible reason for the low number of students continuing with higher level mathematics for the Leaving Certificate. Some students also expressed low mathematical self-concept with regards to higher level mathematics specifically. Students with low prior achievement in mathematics tended to believe that mathematics requires a natural ability which they do not possess. Rote-learning was found to be common among many students in the sample. The most positive image of mathematics held by students was the “problem-solving image”, with resulting implications for the new Project Maths syllabus in post-primary education. Findings from this research study provide important insights into the image of mathematics held by the sample of Irish post-primary students and make an innovative contribution to mathematics education research. In particular, findings contribute to the current national interest in Ireland in post-primary mathematics education, highlighting issues regarding the low uptake of higher level mathematics for the Leaving Certificate and also making a preliminary comparison between students who took part in the piloting of Project Maths and students who were more recently introduced to the new syllabus. This research study also holds implications for mathematics teachers, parents and the mathematics education community in Ireland, with some suggestions made on improving students‟ images of mathematics.